Six Figure Work

ASIC Verification Engineer - New College Grad 2027

NVIDIA

Company websitenvidia.com (NVIDIA, opens in new tab)

Base salary $100,000  to $189,750

Employer-published annual base salary, USD. Advertised base range in Santa Clara, CA

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  • LocationSanta Clara, CA
  • WorkplaceWorkplace not stated
  • Status at last checkSource accepting applications when checked
  • Last checked (47 min ago) · observed since

About this job

Today, NVIDIA is tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in an inclusive, encouraging environment where everyone is inspired to do their best work. Come join the team and see how we can make a lasting impact on the world. 

We are seeking to hire a ASIC Verification Engineer - New College Grad 2027 to contribute to the design verification activities that support the pre-silicon process which ensures proper hardware functionality.  To do so, we simulate the RTL under a variety of conditions to flush out any design bugs as early in the process as possible.
 

What you’ll be doing:

  • Employ cutting edge AI technologies to create automated systems and flows
  • Contribute to complex UVM testbench environments including test development, automation, or analysis
  • Develop directed or random tests in SystemVerilog to verify the reference C++ and RTL models in a simulation environment
  • Debug RTL simulation failures

What we need to see:

  • Pursuing or recently completed a BS, MS, or PhD in EE, CE, or related field (or equivalent experience)
  • Coursework or prior internship exposure to computer architecture, logic design, and/or HDL languages (Verilog, VHDL)
  • Strong programming experience in C++ or SystemVerilog and general understanding of OOP concepts
  • Solid understanding of basic concepts of CPU or SoC architecture.
  • Exceptional analytical skills and problem solving skills

Ways to stand out from the crowd:

  • You're passionate about object oriented programming
  • Experience with HW/SW interactions
  • You're experienced with directed and random functional testing including writing test plans and advised or random diagnostics
  • You have internship or lab experience with GPU or Processor verification / validation or other hardware debug.
  • Ambitious and dedicated with strong communication and interpersonal skills.

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you! 

Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are:
100,000 USD – 166,750 USD for Level 1; and 116,000 USD – 189,750 USD for Level 2.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until November 3, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Source: NVIDIA on Workday · View original posting (opens in new tab)

Pay in context

This role's base floor ($100,000) is above 0% of the 3,580 Engineering (non-software) roles in California listed on this site; 203 others list the same floor. Their median floor is $147,000; the middle half runs from $125,000 to $173,000.

Only jobs on this site count, and each one publishes a base salary of $100,000 or more, so this compares six-figure jobs with each other, not with the whole market. Computed Nov 8, 2026.

This range next to 6 other live NVIDIA roles with the nearest advertised base floor
Chart as a table
This range next to 6 other live NVIDIA roles with the nearest advertised base floor
RolePublished base
ASIC Verification Engineer - New College Grad 2027 (this listing)$100,000 - $189,750
ASIC Verification Engineer, Memory Management - New College Grad 2027$100,000 - $189,750
Low Power ASIC Engineer - New College Grad 2027$100,000 - $189,750
High Speed SerDes Validation Engineer - New College Grad 2026$100,000 - $189,750
Formal Verification Engineer - New College Grad 2027$100,000 - $189,750
GPU Verification Engineer - New College Grad 2026$100,000 - $189,750
ASIC Verification Engineer - New College Grad 2027$100,000 - $189,750

Same $100K to $400K scale as every card. All NVIDIA roles · How to read the bar

Observed changes

  1. First observed on the employer's board
  2. Began meeting the published-salary criteria
Observed since
Employer-stated posting date
2026-10-30
Where this pay comes from

Location as the employer wrote it: US, CA, Santa Clara (Levels 1-2 combined)

100,000 USD – 166,750 USD for Level 1; and 116,000 USD – 189,750 USD for Level 2.

Method
Employer text, read with fixed rules and re-verified
Checked
Rule set
us-base-v2

The pay passage appears in the employer's own job text. Fixed, deterministic rules located it, and the passage below was checked against the stored copy of the posting.

What we verified

  • The pay figures come from the employer's own listing, quoted exactly above.
  • The pay is an annual base salary in US dollars with a minimum of at least $100,000.
  • The role was publicly listed on the employer's job board when last checked.

We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.

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